Dynamic mathematical validation using data mining

ABSTRACT

Provided are techniques for dynamic mathematical validation using data mining. As text is being received, a mathematical statement is identified in the text based on context of the text. A mathematical solution to the mathematical statement is identified in the text based on the context of the text. It is determined that the mathematical solution is incorrect using data mining. In response to determining that auto-correction is to be performed, the mathematical solution is corrected.

FIELD

Embodiments of the invention relate to dynamic mathematical validationusing data mining.

BACKGROUND

A person may send the following statement in an email “our #s went from100 to 120, which was an increase of 26%”. However, going from 100 to120 is not an increase of 26%. Thus, this simple mathematical statementis incorrect. A spell checker does not check for such a mathematicalmistake.

SUMMARY

Provided is a method for dynamic mathematical validation using datamining. The method comprises: as text is being received, identifying amathematical statement in the text based on context of the text;identifying a mathematical solution to the mathematical statement in thetext based on the context of the text; determining that the mathematicalsolution is incorrect using data mining; and, in response to determiningthat auto-correction is to be performed, correcting the mathematicalsolution.

Provided is a computer program product for dynamic mathematicalvalidation using data mining. The computer program product comprises acomputer readable storage medium having program code embodied therewith,the program code executable by at least one processor to perform: astext is being received, identifying a mathematical statement in the textbased on context of the text; identifying a mathematical solution to themathematical statement in the text based on the context of the text;determining that the mathematical solution is incorrect using datamining; and, in response to determining that auto-correction is to beperformed, correcting the mathematical solution.

Provided is a computer system for dynamic mathematical validation usingdata mining. The computer system, comprising: one or more processors,one or more computer-readable memories and one or morecomputer-readable, tangible storage devices; and program instructions,stored on at least one of the one or more computer-readable, tangiblestorage devices for execution by at least one of the one or moreprocessors via at least one of the one or more memories, to performoperations, wherein the operations comprise: as text is being received,identifying a mathematical statement in the text based on context of thetext; identifying a mathematical solution to the mathematical statementin the text based on the context of the text; determining that themathematical solution is incorrect using data mining; and, in responseto determining that auto-correction is to be performed, correcting themathematical solution.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

Referring now to the drawings in which like reference numbers representcorresponding parts throughout:

FIG. 1 illustrates, in a block diagram, a computing environment inaccordance with certain embodiments.

FIG. 2 illustrates, in a block diagram, interaction of a monitoringengine, a natural language engine, and an analytics engine in accordancewith certain embodiments.

FIG. 3 illustrates, in a flow diagram, operations for validating amathematical solution in accordance with certain embodiments.

FIG. 4 illustrates a cloud computing node in accordance with certainembodiments.

FIG. 5 illustrates a cloud computing environment in accordance withcertain embodiments.

FIG. 6 illustrates abstraction model layers in accordance with certainembodiments.

DETAILED DESCRIPTION

The descriptions of the various embodiments of the present inventionhave been presented for purposes of illustration, but are not intendedto be exhaustive or limited to the embodiments disclosed. Manymodifications and variations will be apparent to those of ordinary skillin the art without departing from the scope and spirit of the describedembodiments. The terminology used herein was chosen to best explain theprinciples of the embodiments, the practical application or technicalimprovement over technologies found in the marketplace, or to enableothers of ordinary skill in the art to understand the embodimentsdisclosed herein.

FIG. 1 illustrates, in a block diagram, a computing environment inaccordance with certain embodiments. The computing environment includesa computing device 100. The computing device 100 includes a MathematicalValidation (MV) engine 110 and text 150. The text 150 may be included inany form of communication (e.g., e-mail, text document, spreadsheet,text message, instant message, web form, web forum, broadcast message,table, blog, social post, graphic, chart, other visual, etc.).

In certain embodiments, the MV engine 110 includes a monitoring engine120, a natural language engine 130, and an analytics engine 140 or thefunctionality of these engines 120, 130, 140. In other embodiments, themonitoring engine 120, the natural language engine 130, and theanalytics engine 140 are separate engines that work together.

The MV engine 110 dynamically validates mathematical statements incontext. The mathematical statements may include mathematical equations(e.g., 2+3=5) or may describe mathematical word problems (e.g., “If Idrive 55 miles per hour (mph) for 2 hours, I will travel 110 miles.”).The context may be concurrent (within the text itself) or non-concurrent(in other communications that are separate from the text). The MV engine110 may flag mathematical errors dynamically or may automaticallyprovide contextual mathematical corrections. The MV engine 110determines mathematical solutions automatically for mathematical wordproblems.

The MV engine 110 passively identifies mathematical statements andmathematical solutions that are found within text. In addition, the MVengine 110 automatically and passively validates mathematical statementsto ensure mathematical accuracy. In particular, the MV engine 110 usesan analytics engine to either validate that a mathematical solution iscorrect and or determines that the mathematical solution is incorrect(for flagging to bring this to the attention of a user or for automaticcorrection). The term “passive” is used to indicate that themathematical validation is performed automatically by the MV engine 110,without a specific user request to perform the validation. In certainembodiments, a user may update a setting for passive mathematicalchecking. In certain alternative embodiments, the user may update thesetting to “turn off” the passive mathematical checking and perform amanual check (e.g., by the user selecting a mathematical statement andrequesting a mathematical check). In various embodiments, there may bedifferent options for reviewing/correcting mathematical statements basedon user preferences or administrator preferences. For example, the usermay have a mathematical statement automatically corrected or may set anoption so that the user is provided with information about themathematical errors and solutions (without the automatic correction).

For example, communications may include facts and mathematicalstatements. The following are some examples of mathematical statements:

-   -   “The temperature is so crazy. It dropped 20 degrees since        yesterday. It was a high of 75, and now it's only 45 degrees!”    -   “This is great. Our #s went from 100 to 120, which was an        increase of 26%!”    -   “Add ¼ cup of butter to ¼ cup of water to equal ⅔rds of a cup        total.”    -   “I looked at online maps for our trip to Washington DC this        weekend and saw its 200 miles with an average speed of 55 MPH.        If we leave at 5 am and don't make any stops we should be there        by 7 am.”

FIG. 2 illustrates, in a block diagram, interaction of the monitoringengine 120, the natural language engine 130, and the analytics engine140 in accordance with certain embodiments. The monitoring engine 120looks for predefined characteristics in the text 150 that would indicatea mathematical statement. Examples of predefined characteristics includeboth text and numerical numbers, which may be located in text, tables,graphics, charts, and other visuals. Additional examples of predefinedcharacteristics include mathematical terms indicating a mathematicalsolution (e.g., plus sign (“+”), equal sign (“=”), etc.). Furtherexamples of predefined characteristics include locating a change fromprevious numbers (e.g., increase, decrease, lowered, raised, dropped,times, divided, percentage, total, sum, equals, etc.). In certainembodiments, context may be described as a number of words surroundingpre-defined characteristics.

For example, the monitoring engine 120 may look for the presence of twoor more numbers (both text and numerical numbers). The monitoring engine120 passes on its results to the natural language engine 130.

The natural language engine 130 initiates and evaluates the completetext to determine what key mathematical terms indicate a mathematicalsolution based on the predefined characteristics. For example, if themonitoring engine 120 found numbers, the natural language engine 130determines a mathematical relationship between those previous numbers(e.g., increase, decrease, lowered, raised, dropped, times, divided,percentage, total, sum, equals, etc.). The natural language engine 130passes on its results to the analytics engine 140.

The analytics engine 140 uses data mining to ascertain a fullmathematical statement and mathematical solution in context. In certainembodiments, the data mining is used to ascertain a mathematicalequation in context, even for non-concurrent text or numbers. Forexample, if there is a table with the weather temperatures for lastmonth listed, and the text of a document says its 26% hotter this weekthan last, the data mining would first seek out the dates that wouldalign with that statement, and then look at the table to determine thematch for dates and then validate the mathematical problem. Once thefull mathematical statement and mathematical solution are identified,the analytics engine 140 also validates whether the mathematicalsolution already in the text 150 is mathematically correct.

The MV engine 110 allows a user to define a preference as to whatsubsequent action would occur: either 1) automatic correction or 2)flagging an incorrect mathematical solution.

For automatic correction, the MV engine 110 automatically corrects anymathematical inaccuracies in the text 150. The MV engine 110 may alsoprovide an indication (e.g., via a User Interface (UI)) as to wherecorrections have been made so the user is aware (and may make furtherchanges as desired).

For flagging, the MV engine 110 updates the text 150 (e.g., displayed inthe UI) to indicate the incorrect mathematical solution. In variousembodiments, the MV engine 110 may color code the incorrect mathematicalsolution to reflect its accuracy (e.g., green text=correct, while redtext=incorrect), make the text larger, highlight the incorrectmathematical solution, provide a comment about the incorrectmathematical solution, underline the incorrect mathematical solution,etc. With embodiments, a user may select (e.g., via a right click of amouse when a computer screen displays the text 150, via touching a touchscreen displaying the text 150, etc.) the incorrect mathematicalsolution to see a corrected solution and may select the correctedsolution to replace the existing incorrect mathematical solution.

In addition to looking at surrounding text, the analytics engine 140 mayalso look at tables, graphics, charts, and other visuals to determinewhether the mathematical statements are correct. For example, a sentencemay be listed in the text advising “the chart below indicates anincrease of 50% YTY.” The MV engine 110 identifies this text asindicating a mathematical statement, finds the mathematical statement inthe chart, finds the mathematical solution in the chart, and makes acomparison to the mathematical solution being proposed against datacontained in a table to verify that the mathematical solution iscorrect.

The MV engine 110 improves the accuracy of mathematical statements incommunications to improve the understanding of the receivers. Thisincreases productivity in enabling users to not have to manually checktheir mathematical statements in a different system, but instead havethe mathematical solution check integrated into any communicationtechnique that users are using already.

FIG. 3 illustrates, in a flow diagram, operations for validating amathematical solution in accordance with certain embodiments. Controlbegins at block 300 with the MV engine 110 receiving text. In block 302,the MV engine 110 determines whether a mathematical statement has beenidentified in the context of the text as a user types. If so, processingcontinues to block 304, otherwise, processing continues to block 300.

In certain other embodiments, the user completes typing the text 150 andinputs the text 150 to the MV engine 110 for processing (e.g., byselecting a “mathematical validation” tool or button). In variousembodiments, that text 150 may be provided via voice to text or otherway of documenting text in which a mathematical equation may be present.

In block 304, the MV engine 110 identifies a mathematical solution inthe context of the text for the mathematical statement. In block 306,the MV engine 110 determines whether the mathematical solution iscorrect. If so, processing continues to block 308, otherwise, processingcontinues to block 310. The mathematical solution may be validated usingconcurrent context (within the text itself) or non-concurrent context(in other communications that are separate from the text). That is,determining that the mathematical solution is incorrect may be based oninformation obtained from communications that are separate from thetext.

In block 308, the MV engine 110 determines whether there is more text150 to process. If so, processing continues to block 300, otherwise,processing ends.

In block 310, the MV engine 110 determines whether automatic correctionhas been selected. If so, processing continues to block 312, otherwise,processing continues to block 314.

In block 312, the MV engine 110 automatically corrects the mathematicalsolution and processing continues block 310. In block 314, the MV engine110 flags the incorrect mathematical solution and processing continuesto block 310. In certain embodiments, in response to user selection ofthe flagged mathematical statement, the MV engine 110 provides acorrected mathematical statement, and, in response to user selection ofthe corrected mathematical statement, the MV engine 110 updates the text150 with the corrected mathematical statement.

In certain embodiments, the MV engine 110 allows for approximatedcalculation. Approximated calculation may be used to describe anapproximate solution. An example of an approximated calculation is:“There are 3 votes out of 8 disagreed with the new proposal, which isabout a third.” Mathematically, ⅜ is not ⅓, but it is approximately ⅓.In certain embodiments, the MV engine 110 allows a user to predefine alevel of precision/accuracy for the mathematical statements (e.g., inrules or preferences). Also, in other embodiments, the MV engine 110provides a feature for approximated calculation that may be customizedat the user and/or level. For example, a user may expand and/or narrowhow closely the user wants the accuracy to be for a mathematicalstatement. The MV engine 110 may also allow for users to create newcriteria and rules for identifying and validating mathematicalstatements and mathematical solutions. Using the example approximatedcalculation above, he first time this occurs, ⅓rd may be flagged forreview, but then if a user accepts that as “close enough” then thepreferences are updated by the MV engine 110 and used for futureequations.

Cloud Embodiments

It is understood in advance that although this disclosure includes adetailed description on cloud computing, implementation of the teachingsrecited herein are not limited to a cloud computing environment. Rather,embodiments of the present invention are capable of being implemented inconjunction with any other type of computing environment now known orlater developed.

Cloud computing is a model of service delivery for enabling convenient,on-demand network access to a shared pool of configurable computingresources (e.g.

networks, network bandwidth, servers, processing, memory, storage,applications, virtual machines, and services) that can be rapidlyprovisioned and released with minimal management effort or interactionwith a provider of the service. This cloud model may include at leastfive characteristics, at least three service models, and at least fourdeployment models.

Characteristics are as follows:

On-demand self-service: a cloud consumer can unilaterally provisioncomputing capabilities, such as server time and network storage, asneeded automatically without requiring human interaction with theservice's provider.

Broad network access: capabilities are available over a network andaccessed through standard mechanisms that promote use by heterogeneousthin or thick client platforms (e.g., mobile phones, laptops, and PDAs).

Resource pooling: the provider's computing resources are pooled to servemultiple consumers using a multi-tenant model, with different physicaland virtual resources dynamically assigned and reassigned according todemand. There is a sense of location independence in that the consumergenerally has no control or knowledge over the exact location of theprovided resources but may be able to specify location at a higher levelof abstraction (e.g., country, state, or datacenter).

Rapid elasticity: capabilities can be rapidly and elasticallyprovisioned, in some cases automatically, to quickly scale out andrapidly released to quickly scale in. To the consumer, the capabilitiesavailable for provisioning often appear to be unlimited and can bepurchased in any quantity at any time.

Measured service: cloud systems automatically control and optimizeresource use by leveraging a metering capability at some level ofabstraction appropriate to the type of service (e.g., storage,processing, bandwidth, and active user accounts). Resource usage can bemonitored, controlled, and reported providing transparency for both theprovider and consumer of the utilized service.

Service Models are as follows:

Software as a Service (SaaS): the capability provided to the consumer isto use the provider's applications running on a cloud infrastructure.The applications are accessible from various client devices through athin client interface such as a web browser (e.g., web-based email). Theconsumer does not manage or control the underlying cloud infrastructureincluding network, servers, operating systems, storage, or evenindividual application capabilities, with the possible exception oflimited user-specific application configuration settings.

Platform as a Service (PaaS): the capability provided to the consumer isto deploy onto the cloud infrastructure consumer-created or acquiredapplications created using programming languages and tools supported bythe provider. The consumer does not manage or control the underlyingcloud infrastructure including networks, servers, operating systems, orstorage, but has control over the deployed applications and possiblyapplication hosting environment configurations.

Infrastructure as a Service (IaaS): the capability provided to theconsumer is to provision processing, storage, networks, and otherfundamental computing resources where the consumer is able to deploy andrun arbitrary software, which can include operating systems andapplications. The consumer does not manage or control the underlyingcloud infrastructure but has control over operating systems, storage,deployed applications, and possibly limited control of select networkingcomponents (e.g., host firewalls).

Deployment Models are as follows:

Private cloud: the cloud infrastructure is operated solely for anorganization. It may be managed by the organization or a third party andmay exist on-premises or off-premises.

Community cloud: the cloud infrastructure is shared by severalorganizations and supports a specific community that has shared concerns(e.g., mission, security requirements, policy, and complianceconsiderations). It may be managed by the organizations or a third partyand may exist on-premises or off-premises.

Public cloud: the cloud infrastructure is made available to the generalpublic or a large industry group and is owned by an organization sellingcloud services.

Hybrid cloud: the cloud infrastructure is a composition of two or moreclouds (private, community, or public) that remain unique entities butare bound together by standardized or proprietary technology thatenables data and application portability (e.g., cloud bursting for loadbalancing between clouds).

A cloud computing environment is service oriented with a focus onstatelessness, low coupling, modularity, and semantic interoperability.At the heart of cloud computing is an infrastructure comprising anetwork of interconnected nodes.

Referring now to FIG. 4, a schematic of an example of a cloud computingnode is shown. Cloud computing node 410 is only one example of asuitable cloud computing node and is not intended to suggest anylimitation as to the scope of use or functionality of embodiments of theinvention described herein. Regardless, cloud computing node 410 iscapable of being implemented and/or performing any of the functionalityset forth hereinabove.

In cloud computing node 410 there is a computer system/server 412, whichis operational with numerous other general purpose or special purposecomputing system environments or configurations. Examples of well-knowncomputing systems, environments, and/or configurations that may besuitable for use with computer system/server 412 include, but are notlimited to, personal computer systems, server computer systems, thinclients, thick clients, handheld or laptop devices, multiprocessorsystems, microprocessor-based systems, set top boxes, programmableconsumer electronics, network PCs, minicomputer systems, mainframecomputer systems, and distributed cloud computing environments thatinclude any of the above systems or devices, and the like.

Computer system/server 412 may be described in the general context ofcomputer system executable instructions, such as program modules, beingexecuted by a computer system. Generally, program modules may includeroutines, programs, objects, components, logic, data structures, and soon that perform particular tasks or implement particular abstract datatypes. Computer system/server 412 may be practiced in distributed cloudcomputing environments where tasks are performed by remote processingdevices that are linked through a communications network. In adistributed cloud computing environment, program modules may be locatedin both local and remote computer system storage media including memorystorage devices.

As shown in FIG. 4, computer system/server 412 in cloud computing node410 is shown in the form of a general-purpose computing device. Thecomponents of computer system/server 412 may include, but are notlimited to, one or more processors or processing units 416, a systemmemory 428, and a bus 418 that couples various system componentsincluding system memory 428 to processor 416.

Bus 418 represents one or more of any of several types of busstructures, including a memory bus or memory controller, a peripheralbus, an accelerated graphics port, and a processor or local bus usingany of a variety of bus architectures. By way of example, and notlimitation, such architectures include Industry Standard Architecture(ISA) bus, Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA)bus, Video Electronics Standards Association (VESA) local bus, andPeripheral Component Interconnects (PCI) bus.

Computer system/server 412 typically includes a variety of computersystem readable media. Such media may be any available media that isaccessible by computer system/server 412, and it includes both volatileand non-volatile media, removable and non-removable media.

System memory 428 can include computer system readable media in the formof volatile memory, such as random access memory (RAM) 430 and/or cachememory 432. Computer system/server 412 may further include otherremovable/non-removable, volatile/non-volatile computer system storagemedia. By way of example only, storage system 434 can be provided forreading from and writing to a non-removable, non-volatile magnetic media(not shown and typically called a “hard drive”). Although not shown, amagnetic disk drive for reading from and writing to a removable,non-volatile magnetic disk (e.g., a “floppy disk”), and an optical diskdrive for reading from or writing to a removable, non-volatile opticaldisk such as a CD-ROM, DVD-ROM or other optical media can be provided.In such instances, each can be connected to bus 418 by one or more datamedia interfaces. As will be further depicted and described below,memory 428 may include at least one program product having a set (e.g.,at least one) of program modules that are configured to carry out thefunctions of embodiments of the invention.

Program/utility 440, having a set (at least one) of program modules 442,may be stored in memory 428 by way of example, and not limitation, aswell as an operating system, one or more application programs, otherprogram modules, and program data. Each of the operating system, one ormore application programs, other program modules, and program data orsome combination thereof, may include an implementation of a networkingenvironment. Program modules 442 generally carry out the functionsand/or methodologies of embodiments of the invention as describedherein.

Computer system/server 412 may also communicate with one or moreexternal devices 414 such as a keyboard, a pointing device, a display424, etc.; one or more devices that enable a user to interact withcomputer system/server 412; and/or any devices (e.g., network card,modem, etc.) that enable computer system/server 412 to communicate withone or more other computing devices. Such communication can occur viaInput/Output (I/O) interfaces 422. Still yet, computer system/server 412can communicate with one or more networks such as a local area network(LAN), a general wide area network (WAN), and/or a public network (e.g.,the Internet) via network adapter 420. As depicted, network adapter 420communicates with the other components of computer system/server 412 viabus 418. It should be understood that although not shown, other hardwareand/or software components could be used in conjunction with computersystem/server 412. Examples, include, but are not limited to: microcode,device drivers, redundant processing units, external disk drive arrays,RAID systems, tape drives, and data archival storage systems, etc.

Referring now to FIG. 5, illustrative cloud computing environment 550 isdepicted. As shown, cloud computing environment 550 comprises one ormore cloud computing nodes 410 with which local computing devices usedby cloud consumers, such as, for example, personal digital assistant(PDA) or cellular telephone 554A, desktop computer 554B, laptop computer554C, and/or automobile computer system 554N may communicate. Nodes 410may communicate with one another. They may be grouped (not shown)physically or virtually, in one or more networks, such as Private,Community, Public, or Hybrid clouds as described hereinabove, or acombination thereof. This allows cloud computing environment 550 tooffer infrastructure, platforms and/or software as services for which acloud consumer does not need to maintain resources on a local computingdevice. It is understood that the types of computing devices 554A-Nshown in FIG. 5 are intended to be illustrative only and that computingnodes 410 and cloud computing environment 550 can communicate with anytype of computerized device over any type of network and/or networkaddressable connection (e.g., using a web browser).

Referring now to FIG. 6, a set of functional abstraction layers providedby cloud computing environment 550 (FIG. 5) is shown. It should beunderstood in advance that the components, layers, and functions shownin FIG. 6 are intended to be illustrative only and embodiments of theinvention are not limited thereto. As depicted, the following layers andcorresponding functions are provided:

Hardware and software layer 660 includes hardware and softwarecomponents. Examples of hardware components include mainframes, in oneexample IBM® zSeries® systems; RISC (Reduced Instruction Set Computer)architecture based servers, in one example IBM pSeries® systems; IBMxSeries® systems; IBM BladeCenter® systems; storage devices; networksand networking components. Examples of software components includenetwork application server software, in one example IBM WebSphere®application server software; and database software, in one example IBMDB2® database software. (IBM, zSeries, pSeries, xSeries, BladeCenter,WebSphere, and DB2 are trademarks of International Business MachinesCorporation registered in many jurisdictions worldwide).

Virtualization layer 662 provides an abstraction layer from which thefollowing examples of virtual entities may be provided: virtual servers;virtual storage; virtual networks, including virtual private networks;virtual applications and operating systems; and virtual clients.

In one example, management layer 664 may provide the functions describedbelow. Resource provisioning provides dynamic procurement of computingresources and other resources that are utilized to perform tasks withinthe cloud computing environment. Metering and Pricing provide costtracking as resources are utilized within the cloud computingenvironment, and billing or invoicing for consumption of theseresources. In one example, these resources may comprise applicationsoftware licenses. Security provides identity verification for cloudconsumers and tasks, as well as protection for data and other resources.User portal provides access to the cloud computing environment forconsumers and system administrators. Service level management providescloud computing resource allocation and management such that requiredservice levels are met. Service Level Agreement (SLA) planning andfulfillment provide pre-arrangement for, and procurement of, cloudcomputing resources for which a future requirement is anticipated inaccordance with an SLA.

Workloads layer 666 provides examples of functionality for which thecloud computing environment may be utilized. Examples of workloads andfunctions which may be provided from this layer include: mapping andnavigation; software development and lifecycle management; virtualclassroom education delivery; data analytics processing; transactionprocessing; and mathematical validation processing.

Thus, in certain embodiments, software or a program, implementingmathematical validation processing in accordance with embodimentsdescribed herein, is provided as a service in a cloud environment.

In certain embodiments, the computing device 100 has the architecture ofcomputing node 410. In certain embodiments, the computing device 100 ispart of a cloud environment. In certain alternative embodiments, thecomputing device 100 is not part of a cloud environment.

Additional Embodiment Details

The present invention may be a system, a method, and/or a computerprogram product. The computer program product may include a computerreadable storage medium (or media) having computer readable programinstructions thereon for causing a processor to carry out aspects of thepresent invention.

The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present invention may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, or either source code or object code written in anycombination of one or more programming languages, including an objectoriented programming language such as Smalltalk, C++ or the like, andconventional procedural programming languages, such as the “C”programming language or similar programming languages. The computerreadable program instructions may execute entirely on the user'scomputer, partly on the user's computer, as a stand-alone softwarepackage, partly on the user's computer and partly on a remote computeror entirely on the remote computer or server. In the latter scenario,the remote computer may be connected to the user's computer through anytype of network, including a local area network (LAN) or a wide areanetwork (WAN), or the connection may be made to an external computer(for example, through the Internet using an Internet Service Provider).In some embodiments, electronic circuitry including, for example,programmable logic circuitry, field-programmable gate arrays (FPGA), orprogrammable logic arrays (PLA) may execute the computer readableprogram instructions by utilizing state information of the computerreadable program instructions to personalize the electronic circuitry,in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein comprises anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the block may occur out of theorder noted in the figures. For example, two blocks shown in successionmay, in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

We claim:
 1. A method, comprising: as text is being received,identifying, using a processor of a computer, a mathematical statementin the text based on context of the text using a monitoring engine toidentify predefined characteristics including numbers and a relationshipbetween the numbers; identifying a mathematical solution to themathematical statement in the text based on the context of the text andthe predefined characteristics using a natural language engine;determining that the mathematical solution is incorrect using ananalytics engine and data mining; determining whether auto-correction isto be performed; and in response to determining that auto-correction isto be performed, correcting the mathematical solution.
 2. The method ofclaim 1, further comprising: determining whether flagging is to beperformed; in response to determining that flagging is to be performed,flagging the mathematical solution as incorrect; in response to userselection of the flagged mathematical statement, providing a correctedmathematical statement; and in response to user selection of thecorrected mathematical statement, updating the text with the correctedmathematical statement.
 3. The method of claim 1, wherein identifyingthe mathematical statement further comprises: identifying therelationship based on one of a mathematical term and a change betweenthe numbers.
 4. The method of claim 3, wherein identifying themathematical solution further comprises: evaluating the text todetermine which mathematical terms indicate the mathematical solutionbased on the predefined characteristics.
 5. The method of claim 1,wherein determining that the mathematical solution is incorrect is basedon information obtained from communications that are separate from thetext.
 6. The method of claim 1, wherein software is provided as aservice in a cloud environment.
 7. The method of claim 1, furthercomprising: determining that the mathematical solution is correct basedon an approximated calculation.